The Anti-Fraud Center (ASC) of the Singapore Police Force has partnered with six banks including DBS Bank, United Overseas Bank, Oversea-Chinese Banking Corporation, HSBC Bank, SC Bank and GXS Bank to jointly use Robotic Process Automation (RPA) technology to identify Those who may fall victim to job, investment and other types of scams. Once potential victims are identified, they send text message alerts in the hope of preventing greater financial losses.
During the one-month period from August 15 to September 15, 2023, a joint operation was launched by the police and cooperative banks. During this period, they sent more than 5,000 warning text messages to more than 4,000 possible fraud victims. Through this move, more than 800 ongoing scams were successfully stopped and more than $17.1 million in potential financial losses were avoided. At the same time, they also blacklisted more than 600 PayNow (an inter-bank transfer payment in Singapore) accounts, preventing $70,000 in potential financial losses through information sharing.
Anti-Fraud Center officers teamed up with six banks to launch a month-long joint operation
The joint police operation with partner banks reflects their continued efforts to use innovative methods to protect bank customers and reduce losses for fraud victims. They used robotic process automation (RPA) technology to automate information sharing, information processing, and large-scale sending of SMS alerts. This joint operation between the police and banks significantly increases the scope of external intervention by the police, allowing it to send alerts to more victims in a short period of time, thus preventing further financial losses. In fact, many victims only realize they have been scammed after receiving a text message alert from the police and are advised to stop further transfers immediately.
The role of RPA technology in joint operations:
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Data collection and integration: The work of RPA robots starts with gathering information from various data sources. In this scenario, these sources might include bank transaction records, police reports, customer support call records, etc. RPA robots can extract data from these sources, such as transaction time, amount, beneficiary, etc., and integrate them together to form a complete data set, which makes subsequent analysis and processing more convenient.
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Identify suspicious behavior: Once the data is consolidated, RPA bots can begin analyzing the data to identify possible fraud. This may involve pre-set rules and algorithms, such as looking for unusual transaction patterns (e.g. a large number of small transactions in a short period of time) or checking for characteristics that match known fraud (e.g. a beneficiary account that has been known fraudulent accounts). These rules and algorithms can be continuously updated and optimized based on experience and data.
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Automatically send warnings: When an RPA bot identifies possible fraud, it can automatically send warnings to possible victims. This may include sending text messages, emails, or notifications via apps. This automated warning system can stop many potential victims before a scam occurs, as they can receive warnings before the victim makes further transactions.
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Update blacklist: RPA robots can also be used to automatically update fraud-related blacklists. For example, if a PayNow account is identified as potentially involved in fraud, the RPA bot can automatically add it to a blacklist. This way, other customers who try to transfer money to this account can be alerted and the transaction blocked.
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Continuous monitoring and learning: RPA robots can not only perform one-time tasks, but also continuously monitor new data. For example, it can continuously collect and analyze new transaction data in order to identify new fraud patterns. In addition, RPA robots can adjust their recognition patterns based on new information and trends. This allows RPA systems to continuously learn and improve to more effectively identify and prevent fraud.
In this way, RPA technology can greatly increase the efficiency and speed of identifying and preventing fraud. The successful use of RPA technology also enables the police to share important information about compromised PayNow accounts with partner banks. This information allows the bank to leverage its unique technical capabilities and resources to quickly resolve compromised PayNow accounts. This direct, proactive collaborative action is a powerful response to the continued rise in PayNow abuse.
The police have also been advocating that the public actively participate in combating fraud. They have proposed an action plan called "ACT" to help the public beware of and respond to fraud. ACT stands for Add security features (Add), check for possible signs of fraud (Check), and report fraud (Tell).
The first is to add security features. The public is advised to use security apps like ScamShield, as well as enable two-factor authentication for personal accounts such as banking, social media and Singpass accounts. In addition, transaction limits for online banking (including PayNow) can also be set to reduce the amount of money that may be lost in the event of fraud.
The second step is to check for signs of potential fraud. This can be accomplished by asking questions, verifying the authenticity of personal information and money transfer requests, and checking the legitimacy of online listings and reviews. The public needs to take some time to scrutinize. If something seems too good to be true, it probably is a scam.
The last step is to report (Tell) fraud. If they encounter a scam, members of the public should report it to their bank, ScamShield or the police, and inform others of ongoing scams and preventive measures they can take. In addition, suspected fraudulent pages and/or nicknames should also be reported to the appropriate platform.
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